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| author | nunzip <np.scarh@gmail.com> | 2019-02-28 00:19:40 +0000 |
|---|---|---|
| committer | nunzip <np.scarh@gmail.com> | 2019-02-28 00:19:40 +0000 |
| commit | 0665b7fe0169a1b8126502f8945e4535d3c7c693 (patch) | |
| tree | 342b59a2fdc173bc38a9739795c6f456e17d2060 /lenet.py | |
| parent | cbb551537a2505d8f189a4faf9e8c67fe1753d47 (diff) | |
| download | e4-gan-0665b7fe0169a1b8126502f8945e4535d3c7c693.tar.gz e4-gan-0665b7fe0169a1b8126502f8945e4535d3c7c693.tar.bz2 e4-gan-0665b7fe0169a1b8126502f8945e4535d3c7c693.zip | |
Set state of train_test_split
Diffstat (limited to 'lenet.py')
| -rw-r--r-- | lenet.py | 8 |
1 files changed, 4 insertions, 4 deletions
@@ -143,10 +143,10 @@ def mix_data(X_train, y_train, X_validation, y_validation, train_gen, tr_labels_ val_labels = val_labels_gen else: - X_train_gen, _, y_train_gen, _ = train_test_split(train_gen, tr_labels_gen, test_size=1-split, stratify=tr_labels_gen) - X_train_original, _, y_train_original, _ = train_test_split(X_train, y_train, test_size=split, stratify=y_train) - X_validation_gen, _, y_validation_gen, _ = train_test_split(val_gen, val_labels_gen, test_size=1-split, stratify=val_labels_gen) - X_validation_original, _, y_validation_original, _ = train_test_split(X_validation, y_validation, test_size=split, stratify=y_validation) + X_train_gen, _, y_train_gen, _ = train_test_split(train_gen, tr_labels_gen, test_size=1-split, random_state=0, stratify=tr_labels_gen) + X_train_original, _, y_train_original, _ = train_test_split(X_train, y_train, test_size=split, random_state=0, stratify=y_train) + X_validation_gen, _, y_validation_gen, _ = train_test_split(val_gen, val_labels_gen, test_size=1-split, random_state=0, stratify=val_labels_gen) + X_validation_original, _, y_validation_original, _ = train_test_split(X_validation, y_validation, test_size=split, random_state=0, stratify=y_validation) train_data = np.concatenate((X_train_gen, X_train_original), axis=0) train_labels = np.concatenate((y_train_gen, y_train_original), axis=0) val_data = np.concatenate((X_validation_gen, X_validation_original), axis=0) |